code: def benchmark_gaussian_noise(
      num_samples,
      batch_size,
      jit_compile=True,
  ):
      layer_name = "GaussianNoise"
      init_args = {
          "stddev": 0.5,
      }
      benchmark = LayerBenchmark(
          layer_name,
          init_args,
          input_shape=[256, 256, 4],
          jit_compile=jit_compile,
      )
  
      benchmark.benchmark_predict(
          num_samples=num_samples,
          batch_size=batch_size,
      )
  
      benchmark.benchmark_train(
          num_samples=num_samples,
          batch_size=batch_size,
      )
  
file_path: keras/benchmarks/layer_benchmark/regularization_benchmark.py
imports: from absl import app
  from absl import flags
  from benchmarks.layer_benchmark.base_benchmark import LayerBenchmark
label_desc: Use image node_id 3 for calling a global function with example usage: benchmark_gaussian_noise(num_samples, batch_size, jit_compile) without return types